Provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context.
Provides read-only MCP tools for hybrid semantic and keyword search over locally indexed PDF documentation, with citations and context retrieval for LLM agents.
Enables AI assistants to access and search MkDocs documentation through tools for full-text search, page navigation, and code block extraction. It serves documentation pages as readable resources and provides structural outlines to help LLMs navigate documentation content.
Provides direct access to local documentation files through simple search and overview tools, enabling LLMs to query project-specific markdown documentation without requiring vector databases or RAG pipelines.
Provides tools for AI agents to search, browse, and retrieve the full documentation for the mcp-framework. It enables agents to access documentation sections and page content directly within MCP-compatible environments like Claude Code and Cursor.